First find the decimal equivalent of square root 3: SQRT(3) = 1.732 ( roughly)
If the base and height were each 3, then the hypotenuse would need to be:
3^2 + 3^2 = C^2
9 + 9 = C^2
18 = C^2
C = SQRT(18) = 4.24
This is larger than sqrt(3), so this cannot be a right triangle.
If one leg was 3 and the other leg was sqrt(3) then the hypotenuse would be:
3^2 + 1.73^2 = C^2
9 + 3 = C^2
12 = C^2
C = SQRT(12) = 3.46
This is larger than 3, this cannot be a right triangle.
The answer is b) no.
It’s A. The first option. Also pls brainlist
Answer:
The point estimate for p is 0.86.
Step-by-step explanation:
We are given that in a marketing survey, a random sample of 730 women shoppers revealed that 628 remained loyal to their favorite supermarket during the past year (i.e. did not switch stores).
Let p = <u><em>proportion of all women shoppers who remain loyal to their favorite supermarket</em></u>
Now, the point estimate for the population proportion (p) is represented by ;
Point estimate for p =
=
where, X = Number of women shoppers who remained loyal to their favorite supermarket during the past year = 628
n = sample of women shoppers = 730
So, <u>point estimate for p</u> (
) =
=
= <u>0.86</u>
The distribution function of the univariate random variable x is continuous at x if and only if , F (x) = P (X ≤ x)
Continuous univariate statistical distributions are functions that describe the likelihood that a random variable, say, X, falls within a given range. Let P (a Xb) represent the probability that X falls within the range [a, b].
A numerically valued variable is said to be continuous if, in any unit of measurement, whenever it can take on the values a and b. If the random variable X can assume an infinite and uncountable set of values, it is said to be a continuous random variable.
If X can take any specific value on the real line, the probability of any specific value is effectively zero (because we'd have a=b, which means no range). As a result, continuous probability distributions are frequently described in terms of their cumulative distribution function, F(x).
To learn more about univariated data
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